Trusted Data Engineering Company
Hire Data Engineers for USA, Europe & GCC
Build the data infrastructure that powers your analytics, AI, and business decisions with DH Solutions. Our data engineers help startups, enterprises, and data-driven businesses build ETL pipelines, cloud data warehouses, data lakes, real-time streaming systems, dbt transformation layers, and scalable data platforms on AWS, Azure, and GCP — for the USA, Europe, UAE, Saudi Arabia, Qatar, Kuwait, Oman, Bahrain, and international markets.
Get expert help for your project.
Why Businesses Choose Our Data Engineers
Our data engineers build the reliable, scalable data infrastructure that your analytics, BI, and AI initiatives depend on — combining modern tooling, cloud-native architecture, and software engineering rigour to deliver data platforms that your team can trust and your business can grow on.
Modern Stack Proficiency
Spark, Kafka, Airflow, dbt, Snowflake, Databricks, Delta Lake — our engineers work with the tools that modern data teams actually use, not legacy ETL platforms that slow you down.
Batch & Real-Time Coverage
Whether you need nightly batch loads into your data warehouse or millisecond-latency streaming for fraud detection — our engineers design the right architecture for your throughput and latency requirements.
Software Engineering Rigour
We treat data pipelines as software — version control, CI/CD, unit testing with dbt, data quality checks, and observability built in from day one rather than bolted on after incidents.
Global Delivery
We build data platforms for businesses across the USA, Europe, GCC, and other international markets — with multi-region data residency, compliance configurations, and cloud-native deployments where needed.
What we build
Data Engineering Services
From ETL pipelines and data warehouses to data lakes, real-time streaming, dbt transformations, data platform engineering, data quality, and governance — our engineers cover the complete data infrastructure stack.
ETL & Data Pipeline Development
Batch and streaming ETL pipelines that extract from source systems, transform with business logic, and load into your data warehouse or lake — built with Airflow, AWS Glue, Azure Data Factory, or custom Python.
Data Warehouse Development
Cloud data warehouses on Snowflake, Redshift, BigQuery, or Azure Synapse — dimensional modelling, star schemas, slowly changing dimensions, and optimised query performance for analytical workloads.
Data Lake & Lakehouse Architecture
Scalable data lakes on S3, ADLS, or GCS with Delta Lake or Apache Iceberg for ACID transactions — centralised raw and curated data storage powering analytics, ML, and BI across your organisation.
Real-Time Streaming Pipelines
Event-driven streaming architectures using Apache Kafka, Apache Flink, Spark Structured Streaming, AWS Kinesis, and Azure Event Hubs — for live dashboards, fraud detection, and real-time operational analytics.
dbt Transformation Layer
SQL-based data transformations, testing, and documentation with dbt — building a reliable, version-controlled, modular transformation layer on top of your data warehouse that data analysts can trust and maintain.
Data Platform Engineering
End-to-end data platform design on Microsoft Fabric, Databricks, or AWS — Lakehouse architecture, data governance, data cataloguing with Unity Catalog, and self-service analytics infrastructure for your organisation.
Data Quality & Observability
Data quality frameworks with Great Expectations, Monte Carlo, or dbt tests — schema validation, freshness checks, anomaly detection, lineage tracking, and alerting to catch data issues before they reach dashboards.
Data Governance & Security
Data cataloguing, column-level security, row-level filtering, PII masking, data lineage documentation, and compliance configurations for GDPR, HIPAA, and PCI-DSS — governing your data estate at scale.
Tools & technologies
Data Engineering Tech Stack We Work With
Our data engineers are proficient across the full modern data engineering toolchain — distributed processing, stream processing, orchestration, transformation, cloud data warehouses, and all three major cloud platforms.
Apache Spark
Apache Kafka
Python
Airflow
dbt
SnowflakeDatabricks
AWSAzure
GCP
PostgreSQL
GitSectors we serve
Industries Our Data Engineers Work In
We have built data platforms across a wide range of industries — each with unique data volumes, latency requirements, compliance standards, and analytical needs our engineers understand deeply.
How to work with us
Flexible Data Engineer Engagement Models
Choose the model that fits your data maturity, team size, and budget. All models include full NDA coverage, IP protection, and a dedicated account manager.
Dedicated Data Engineer
Most PopularHire one or more data engineers who work exclusively on your data platform. Full-time, part-time, or multiple engineers — you control the pipeline roadmap and data infrastructure priorities.
- ✓Full-time or part-time availability
- ✓Direct communication with your team
- ✓Flexible scaling as your data grows
- ✓Monthly billing, no long-term lock-in
Fixed-Price Data Project
Best for Defined ScopeShare your data requirements, we scope, build, and deliver. Ideal for pipeline builds, data warehouse migrations, dbt transformation layer development, or streaming system implementations.
- ✓Fixed cost, no surprise invoices
- ✓Milestone-based delivery
- ✓Ideal for pipeline and platform builds
- ✓Clear deliverables and timeline
Dedicated Data Team
Best for ScaleA complete data team — data engineers, analytics engineers, and a project manager — building and maintaining your entire data platform as a fully embedded, dedicated unit.
- ✓Full team: data engineers, analytics engineers, PM
- ✓Agile delivery with weekly sprints
- ✓Dedicated account manager
- ✓Scales from 2 to 10+ engineers
Why us
DH Solutions vs Freelancers vs Other Agencies
See why data teams and businesses across the USA, Europe, and GCC choose DH Solutions over freelance data engineers or generic data consulting agencies.
| Feature | DH Solutions | Freelancer | Other Agency |
|---|---|---|---|
| Spark, Kafka & Cloud Data Platform Expertise | ✓ | Varies | Varies |
| dbt, Snowflake & Real-Time Streaming Experience | ✓ | Varies | Varies |
| Vetted & Interviewed | ✓ | ✗ | Sometimes |
| Time Zone Overlap | ✓ | Varies | Varies |
| Dedicated Account Manager | ✓ | ✗ | Rarely |
| Flexible Engagement Models | ✓ | ✗ | Sometimes |
| Scale Up / Down Anytime | ✓ | ✗ | ✗ |
| NDA & IP Protection | ✓ | Sometimes | Sometimes |
| Clutch-Verified Reviews | ✓ | ✗ | Varies |
How we work together
Our Data Engineer Hiring Process
From your first message to a data engineer actively building your data platform — a clear, fast process with no ambiguity at any step.
Share your brief
Tell us your data stack, pipeline requirements, and goals. We respond within one business day.
Candidate matching
We shortlist 2–3 pre-vetted data engineers whose skills match your exact stack and requirements.
Interview & select
You interview your chosen candidates. We coordinate, you decide who joins your team.
Onboarding
We handle contracts and setup. Your data engineer is building pipelines within 48 hours.
Ongoing support
A dedicated account manager checks in regularly. Scale up or adjust the team any time.
48h
First profiles sent
3 days
Avg. time to hire
5.0/5
Clutch rating
Common questions
Frequently Asked Questions
Everything you need to know about hiring data engineers from DH Solutions.
How much does it cost to hire a data engineer?
The cost depends on your engagement model and project scope. Dedicated data engineers start from a competitive monthly rate. Contact us for a custom quote based on your requirements.
How quickly can I hire a data engineer from DH Solutions?
You can receive shortlisted data engineer profiles within 48 hours of submitting your brief. Most clients complete interviews and onboarding within 3–5 business days.
What data engineering tools do your engineers specialise in?
Our engineers are proficient in Apache Spark, Apache Kafka, Apache Airflow, dbt, Snowflake, Databricks, Delta Lake, AWS Glue, Azure Data Factory, BigQuery, Redshift, and Python — matched to your existing stack.
Can your data engineers build real-time streaming pipelines?
Yes. We design and build real-time streaming systems using Apache Kafka, Apache Flink, Spark Structured Streaming, AWS Kinesis, and Azure Event Hubs — for event-driven analytics, fraud detection, and live dashboards.
Do your data engineers work with dbt?
Yes. Our engineers are proficient in dbt for SQL-based transformations, testing, and documentation — building reliable, version-controlled, modular transformation layers on top of your data warehouse.
Do your data engineers work in my time zone?
Yes. Our engineers offer flexible working hours with overlap across USA (EST/PST), Europe (CET/GMT), and GCC time zones for smooth daily collaboration.
What Our Clients Say
Verified feedback from our clients on Clutch.
Our process.
Simple, seamless,
streamlined.
Step 1
Step 1: Discuss Your Requirements
We start by understanding your goals, scope, timeline, budget, and vision. We'll also help you choose the best engagement model for your project.
Step 2
Step 2: Create a Plan
We put together a clear delivery roadmap, assign the right engineers and specialists, set milestones, and define success metrics for your product.
Step 3
Step 3: Get to Work
Our team starts design and development, shares progress frequently, gathers your feedback, and iterates until everything is ready to launch.
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